Search

European approaches to fire hazard assessment of facade insulation systems were analyzed. It was established that a number of national normative documents have been adopted in European countries, which mainly set requirements for classes in terms of “reaction to fire” to their constituent elements. A number of European countries have additional requirements regarding characteristics of the resistance of composite facade insulation systems to surficial fire propagation. It was revealed that twelve test methods were used to evaluate this characteristic, four of which are defined as tests with moderate thermal influence, but remaining eight ones were determined as tests with sever thermal influence. Two methods assume a fire scenario outdoors, but the other ten test methods assume fire scenarios indoors. Configurations of the test benches were considered; constructions of six of them contain a wall, but six other constructions are structures of an inner corner formed by several walls. Most test bench configurations provide a fire scenario that corresponds to the exit of a fire fumes plume through an opening in the outer surface of the house that rises along the surface of the facade system in the area immediately above the opening. The characteristics recorded during the tests were considered, there are nine of them in total in the twelve methods, the main of which for most test methods are fire propagation in the vertical and horizontal directions as well as its propagation inside. The intentions to develop a single method for testing resistance of composite facade insulation systems to fire propagation for the European Union member states were emphasized. It is concluded that further studies related to the comparative analysis of approaches to fire tests, including the resistance of composite facade insulation systems to fire, in European countries and in Ukraine according to the currently used method in order to allow acceptability of the latter as basic during the development of the relevant draft national standard of Ukraine.

Funding Information: This work was funded by the Academy of Finland project no: 289037 and the Finnish Fire Protection Fund ( Palosuojelurahasto ). The authors would also like to acknowledge CSC-IT center for Science, Finland and Aalto Science-IT project for the large amount of computational resources provided for the study. We would also like to thank Prof. Haukur Ingason and Dr. Rickhard Hansen for providing us with test data for the SP tunnel fire tests. Funding Information: This work was funded by the Academy of Finland project no: 289037 and the Finnish Fire Protection Fund (Palosuojelurahasto). The authors would also like to acknowledge CSC-IT center for Science, Finland and Aalto Science-IT project for the large amount of computational resources provided for the study. We would also like to thank Prof. Haukur Ingason and Dr. Rickhard Hansen for providing us with test data for the SP tunnel fire tests. Publisher Copyright: © 2021 The Authors The requirements for the occurrence of travelling fires and their distinction from previously recognized stages of fire development are not well understood. Here we present a CFD method that couples a fuel-area correction to a single-step wood pyrolysis model. The model was validated using SP medium-scale tunnel, demonstrating 19% under-prediction in peak HRR, and BST/FRS large-scale compartment where the predicted temperatures were within ±6% of the measurements. Detailed simulations of compartment geometries identified three modes of fire propagation: (1) With high ceiling heights, the ignition was followed by a fuel-controlled spread/travelling at speeds

Wildfires occur traditionally in the southern situated countries of Europe. However, in the last few years northern states are experiencing wildland fires (vegetation fires) which sustain their propagation for more than few hours. Reasons for this new situation have been discussed during the CMINE Wildfire Task Group meetings (DRIVER+ project with a mandate of one year—2019). In our paper we will summarize our main findings, which refer to two basic topics—landscape management and climate change. There are more and more parcels of land which have become abandoned because of numerous reasons, but the outcome is the same. The absent people are not cutting the trees, and the people do not bring their cattle or sheep to graze the grass and shrubs. This vegetation grows every spring and lies down on the ground every autumn as potential fire propagation fuel waiting for an ignition. Climate change is another global issue which is creating dangerous weather conditions with extreme high temperatures during the summer season plus mild winters, which is leading to wildfire occurrence in some parts of Europe year round. In our paper we will describe two case studies from Portugal and South Wales, having the same conclusions—no land management strategy and extreme weather are the best conditions for life threatening wildfires.

A fire has been analyzed in a real underground coal mine, using a sublevel method, duringan entire year. The study was focused on the collapsed area, reproducing a real mixture formed bycoal, waste, and air gap. The analysis was done by means of an experimental analysis, a computationalfuid dynamic model (CFD), and simulations using a mine ventilation software. Three scenarios weredetermined and studied regarding their influence on the evolution of the fire: (a) development ofthe fire without taking any action, (b) sealing offthe affected areas, and (c) sealing and reducing theventilation in the affected area and surrounding drifts. The study revealed the behavior of the fire ina real mine and the effectiveness of the main fire-fighting measures over time, verifying that none ofthe measures taken could eliminate the fire-induced in the collapsed area. This research was funded by the Junta de Castilla y León (Spain), project LE167G18, as well as the European Union through the programs ECSC and RFCS, grant numbers 7220-PR/061 and RFCR-CT-2010-00005.

Much of the early research which now underpins tunnel fire safety design was carried out experimentally, using small scale ducts. This paper reviews such experiments, mostly carried out in the 1960s, 1970s, and 1980s, highlighting the assumptions and limitations of the early studies, which may have been forgotten as the equations developed have been applied in practice in the subsequent years. The review covers three primary topics; fire propagation under ‘turbulent slug flow’ conditions, stratification & flame spread, and backlayering & critical ventilation velocity.

Coupled CFD fire simulations and thermomechanical FE analyses typically consist of fire simulations, heat transfer analyses and structural response analyses, mutually coupled by three coupling steps. There are two coupling approaches, one-way and two-way coupling, where two-way coupling includes the effects of the structural response on fire propagation. In the first part of this paper, one- and two-way coupling approaches including the coupling steps are proposed to include coupling at the structural level. Then a case study comprising an office space with a 12-plate thin-walled steel façade under fire conditions is introduced, as well as the related CFD and FE models. A newly developed automated coupling interface and subprograms are used to perform several one-way and two-way coupled analyses using a coarse and fine CFD mesh for the case study. Slight differences are found in the results of identical simulations due to random effects in the fire simulations. Nevertheless, it can be concluded that two-way coupling is feasible, and that significant differences in the façade failure progression illustrate its effectiveness. Future research includes additional developments of both the fire and structural models, as well as verification and parametric studies to further confirm the findings.

The thermo-chemical processes of coal spontaneous combustion in a practical inclined outcrop seam were investigated in order to understand underground mineral self-ignition, fire propagation, and reserves loss. A heat and mass transfer model of porous coal-bearing stratum was employed, combining convection and radiation with transient exothermic source which is coupled with coal oxidation, oxygen supply, and fuel consumption. It is found that spontaneous combustion firstly occurs under lean oxygen condition and fire development controlled by the reaction heat release in the early oxidation process shifts to oxygen restriction after coal self-ignition. The stratum porosity affects significantly the fire propagation. Fire propagation rate slightly increases as the inclined angle decreases. Compared with indirect surface survey, the predicted reverses loss is more reasonable; and thus, the present model could provide a useful reference to loss estimation in coal fire hazards.

Since the dawn of history maritime transport was an essential part of human communication and development which mandates the rapid development of the ship industry. It was accompanied by disasters caused by several factors among them fire played an important role. Fire can cause structural damage which affects ship safety and smoke which is life threating to passengers and ship crow. Trapped smoke in ship compartments if not ventilated or released can reach higher temperatures leading to flashover situation which enable fire propagation. The FLUENT CFD calculations were performed to analyze smoke generation and propagation in closed ship compartments. The time to reach flashover is also calculated. Based on how sealed and tight the compartment is three different scenarios where studied in this analysis: running air-condition while compartment door is open, stopped air-condition while compartment door is closed, and finally running air-condition while compartment door is closed. The calculations show that, the last scenario which incorporates modified running air-condition scheme to mitigate smoke was the best scenario.

This paper aims to develop a two-layer emergency logistics system with a single depot and multiple demand sites for wildfire suppression and disaster relief. For the first layer, a fire propagation model is first built using both the flame-igniting attributes of wildfires and the factors affecting wildfire propagation and patterns. Second, based on the forecasted propagation behavior, the emergency levels of fire sites in terms of demand on suppression resources are evaluated and prioritized. For the second layer, considering the prioritized fire sites, the corresponding resource allocation problem and vehicle routing problem (VRP) are investigated and addressed. The former is approached using a model that can minimize the total forest loss (from multiple sites) and suppression costs incurred accordingly. This model is constructed and solved using principles of calculus. To address the latter, a multi-objective VRP model is developed to minimize both the travel time and cost of the resource delivery vehicles. A heuristic algorithm is designed to provide the associated solutions of the VRP model. As a result, this paper provides useful insights into effective wildfire suppression by rationalizing resources regarding different fire propagation rates. The supporting models can also be generalized and tailored to tackle logistics resource optimization issues in dynamic operational environments, particularly those sharing the same feature of single supply and multiple demands in logistics planning and operations (e.g., allocation of ambulances and police forces). © 2017 The Author(s)

Fire propagation models simulate wildfires forward in time from a set of ignition locations, but are usually unable to be used backwards if only a final fire perimeter is available. This approach is useful to search fire ignition points, reconstruct past fire events, adjust fire simulators and other purposes. This study proposes three different algorithms: a short time range backwards in time simulation from the perimeter, a statistical analysis related to the likelihood of a fire ignition location over the domain, and an analysis aiming to multiple ignition locations. The methods presented are fast to be solved and may be used with any empirical fire propagation model as a core engine as long as the ROS is locally defined and the model is not coupled to the weather.

Forest fire causes significant damages to environment and living organisms. It becomes troublesome to recover from the consequences of forest fire. The early and accurate prediction of forest fire propagation in forest area will help in fire management efforts. The models required for prediction of forest fire spread requires many parameters and which are not known precisely during the emergency. So there is a need of intelligent system to model and predict the propagation of forest fire to reduce the consequences of forest fire and minimize the management efforts. In this work, we have discussed different techniques available in literature for forest fire prediction. This paper also describes the implementation and analysis of prediction of forest fire propagation using Genetic Algorithm and Geometric Semantic Genetic Programming.

In this chapter, the cases of the extreme wildfires and disasters that occurred in Portugal in 2013 (Picoes and Caramulo) and in 2017 (Pedrogao Grande and Central Region), their fire environment, fire propagation, and impacts are described. The Portuguese experience is complemented with other cases that occurred in Greece, Italy, Australia, USA, and Canada, which are described following different fire management approaches. These cases put in evidence the complexity involved in managing these increasingly frequent extreme fire events.

Considering the importance of forest fires problem in Italy, It is essential to improve the tools available for forest fire prevention, beginning with a correct and detailed fire risk evaluation. At present most part of forest fire plans at national level, do not consider, when dealing with forest fire risk analysis, fire’s behavior and potential propagation (or consider them only using empirical models). This study shows the methodology used by the Veneto Region for the characterization and mapping of forest fire risk at regional level. The application of forest fire propagation simulation allowed the creation of very detailed maps and the acquisition of important information about potential fire intensity, something not possible using only empirical methods

Forests are a natural renewable resource and can meet the needs of the society, provided that they are used for a multiple, rational, continuous and sustainable use. Forest fires are a natural component of forest ecosystems and cannot be completely eliminated. However, in recent decades, there has been a tendency to transform forest fires from a natural regulatory factor into a catastrophic phenomenon causing significant economic, environmental and social damage. It is critical to understand the relationships between the underlying environmental factors and spatial behaviour of a forest fire in order to develop effective and scientifically sound forest fire management plans. The key objective of this study is to enhance the efficiency of the formation of a real-time forest fire forecast under the unsteady and uncertain conditions. In the article, the author proposes to develop an intelligent system for predicting the forest fire development based on artificial intelligence and deep computer-aided learning. A key element of the system is forest fire propagation models that recognise data from successive images, predict the forest fire dynamics and generate an image with a fire propagation forecast. It is proposed to build forest fire propagation models by using a real-time forest fire forecasting method. In the article, the author presented a structural diagram of an intelligent system to forecast the dynamics of a forest fire and described the functional structure of the system by constructing its functional models in the form of IDEF0 diagrams.

The data presented in this article are related to research article “Investigation on thermal and fire propagation behaviors of multiple lithium-ion batteries within the package” (Chen et al., 2019). This data article provides the data information including the experiment pictures, flame temperatures, pressure and heat flux sensors temperatures, and gas concentrations of 6 × 6 batteries and 10 × 10 batteries. The video of the whole thermal and fire propagation behaviors of 6 × 6 batteries is also provided. Keywords: Lithium-ion battery, Pack, Thermal behavior, Fire propagation

Predicting the propagation of forest fires is a crucial point to mitigate their effects. Therefore, several computational tools or simulators have been developed to predict the fire propagation. Such tools consider the scenario (topography, vegetation types, fire front situation), and the particular conditions where the fire is evolving (vegetation conditions, meteorological conditions) to predict the fire propagation. However, these parameters are usually difficult to measure or estimate precisely, and there is a high degree of uncertainty in many of them. This uncertainty provokes a certain lack of accuracy in the predictions with the consequent risks. So, it is necessary to apply methods to reduce the uncertainty in the input parameters. This work presents a comparison of ESSIM-EA and ESSIM-DE: two methods to reduce the uncertainty in the input parameters. These methods combine Evolutionary Algorithms, Parallelism and Statistical Analysis to improve the propagation prediction.

Fire safe design requires a builder, architect or fire safety engineer to ensure that the available safe escape time (ASET) exceeds the required safe escape time (RSET), for which an estimate of toxic hazard from smoke is required. In Europe, the burning behaviour of construction products must be tested and labelled according to their Euroclass, based on their fire performance in a range of tests. Each Euroclass can be used to indicate a mass loss range. The yields of toxic products may be determined for each material as a function of fire condition. Reliable data has been widely reported from the steady state tube furnace (ISO TS 19700) and the fire propagation apparatus (ISO 12136) for both well-ventilated and under-ventilated flaming. By combining the toxic product yields, most easily expressed as an LC 50 , with the mass loss range, a methodology is proposed for quantifying the volume of toxic effluent produced by burning construction materials within an enclosure. This allows a maximum safe loading of construction materials to be quantified for a given volume of enclosure. This is intended to ensure that estimates of toxic hazard are undertaken as part of any fire hazard assessment, not to replace more rigorous engineering analyses. It will allow architects and builders to ensure that their materials’ selection does not compromise fire safety.

Chile ha tenido un notable aumento en el riesgo de incendios de interfaz urbano-forestal. También se ha constatado un elevado nivel de daños producidos por la propagación del fuego en estas áreas. Ello se ha debido, entre otros factores, por las prolongadas sequías asociadas a condiciones meteorológicas muy desfavorables, el aumento de la intencionalidad en la iniciación de incendios, debilidades en las campañas de prevención y manejo de la vegetación combustible, y también por deficiencias en las políticas de gestión del territorio. En este artículo se describen las principales instituciones que se encargan de proteger al país frente a este problema.

Recently, deployment of large-capacity diesel haulage trucks is rapidly increasing in the domestic large-opening limestone mines due to the high level of operational flexibility. However, in multi-...

The scope of wildfires over the previous decade has brought these natural hazards to the forefront of risk management. Wildfires threaten human health, safety, and property, and there is a need for comprehensive and readily usable wildfire simulation platforms that can be applied effectively by wildfire experts to help preserve physical infrastructure, biodiversity, and landscape integrity. Evaluating such platforms is important, particularly in determining the platforms&rsquo, reliability in forecasting the spatiotemporal trajectories of wildfire events. This study evaluated the predictive performance of a wildfire simulation platform that implements a Monte Carlo-based wildfire model called WyoFire. WyoFire was used to predict the growth of 10 wildfires that occurred in Wyoming, USA, in 2017 and 2019. The predictive quality of this model was determined by comparing disagreement and agreement areas between the observed and simulated wildfire boundaries. Overestimation&ndash, underestimation was greatest in grassland fires (&gt, 32) and lowest in mixed-forest, woodland, and shrub-steppe fires (&lt, &minus, 2.5). Spatial and statistical analyses of observed and predicted fire perimeters were conducted to measure the accuracy of the predicated outputs. The results indicate that simulations of wildfires that occurred in shrubland- and grassland-dominated environments had the tendency to over-predict, while simulations of fires that took place within forested and woodland-dominated environments displayed the tendency to under-predict.

In this study, the characteristics of fires in case of two vehicles in a tunnel are analyzed by Computational Fluid Dynamics analysis for varying tunnel aspect ratios. Unsteady heat release rates over time are set as the input conditions of fire sources considering real phenomena. Unsteady heat release rate values are obtained from experiments. As a result, the smoke velocities above the fire source appear faster in the case of tunnels with a large aspect ratio because the higher the height of the tunnel, the faster the smoke velocity caused by buoyancy forces. The smoke velocity in the longitudinal direction increases quickly. However, the temperature distribution in the vicinity of the ceiling is low when the tunnel aspect ratio is large because the height of the tunnel is not directly affected by the flames. Also, the higher the height of the tunnel, the lower the visibility distance due to the heat and smoke coming down along the wall surface. However, in the tunnels represented in this study, it is considered that the visibility of evacuees is sufficiently secured.

This paper presents the evaluation of several fire propagation models using a large set of observed fires. The observation base is composed of 80 Mediterranean fire cases of different sizes, which come with the limited information available in an operational context (burned surface and approximative ignition point). Simulations for all cases are carried out with four different front velocity models. The results are compared with several error scoring methods applied to each of the 320 simulations. All tasks are performed in a fully automated manner, with simulations run as first guesses with no tuning for any of the models or cases. This approach leads to a wide range of simulation performance, including some of the bad simulation results to be expected in an operational context. Disregarding the quality of the input data, it is found that the models can be ranked based on their performance and that the most complex models outperform the more empirical ones. Data and source codes used for this paper are freely available to the community.

Recent wildland urban interface fires have demonstrated the unrelenting destructive nature of these events and have called for an urgent need to address the problem. The Wildfire paradox reinforces the ideology that forest fires are inevitable and are actually beneficial; therefore focus should to be shifted towards minimizing potential losses to communities. This requires the development of vulnerability-based frameworks that can be used to provide holistic understanding of risk. In this study, we devise a probabilistic approach for quantifying community vulnerability to wildfires by applying concepts of graph theory. A directed graph for community in question is developed to model wildfire inside a community by incorporating different fire propagation modes. The model accounts for relevant community-specific characteristics including wind conditions, community layout, individual structural features, and the surrounding wildland vegetation. We calibrate the framework to study the infamous 1991 Oakland fire in an attempt to unravel the complexity of community fires. We use traditional centrality measures to identify critical behavior patterns and to evaluate the effect of fire mitigation strategies. Unlike current practice, the results are shown to be community-specific with substantial dependency of risk on meteorological conditions, environmental factors, and community characteristics and layout.

The paper presents a model to support evacuation plans design for fire emergency management in healthcare facilities. It relies on existing path analysis algorithms such as Dijkstra and fire propagation simulation, also evaluating the level of criticality typical of healthcare facilities such as patients’ speed based upon their illness and admission and architectural structure of wards. The algorithm automatically evaluates the safest evacuation path (which may not coincide with the shortest) for single typology of patient (ambulating, partially-ambulating, completely non-ambulating, auto-sufficient or not) and inpatient unit (ICU, ordinary ward, short-observation unit) in relation to the position of the fire trigger. The results of the algorithm are shown by using SVG-rendered graphic of existing hospital’s layout.

Every year, forest and wildland fires affect more than 350 million hectares worldwide resulting in important environmental, economic, and social losses. To efficiently fight against this major risk, specific actions are deployed. The efficiency of these actions is tightly linked to the knowledge of the phenomena and in improving the tools for detecting, predicting, and understanding fire propagation. An important step for vision-based fire analysis, is the detection of fire pixels. In this work, we propose Deep-Fire a deep convolutional neural network for fire pixels detection and fire segmentation. The proposed technique is tested on a database of wildland fires. The obtained results, show that the proposed architecture gives a very high performance for the segmentation of wildland and forest fire areas in outdoor non-structured scenarios.

a b s t r a c t Fire danger assessment is a vital issue to alleviate the impacts of wildland fires. In this study, a fire danger assessment system is proposed, which extensively uses geographical databases to characterize the spatial variations of fire danger conditions in Iran. This assessment requires three steps: (i) generation of the required input variables, (ii) methods to integrate those variables for creating synthetic indices and (iii) validation of those indices versus fire occurrence data. This fire danger model is based on previous works but adapted to Iranian conditions. It includes an estimation of the fire ignition potential (both considering human and climatic factors) and fire propagation potential. The former was generated from a logistic regression approach based on a wide range of input variables. The fire propagation probability was estimated from the Flammap fire behavior model. A first stage for validation of our fire danger system was based on comparing the estimated danger values to actual fire occurrence, based on satellite detected active fires and burned areas. The logistic regression model for fire ignition probability estimated 72.7% of true ignitions. Detected hotspots occurred more frequently in areas with higher fire ignition probability (average value: 0.65) than non hotspots (average value: 0.4). Propagation probability showed higher values for areas with higher proportion of burned area (r = 0.68, p < 0.001). © 2015 Elsevier B.V. All rights reserved.

Fire presents the process of the uncontrolled combustion that makes material damage and endangers human lives. It is important to know the factors that fire depends on for success projecting and realization of fire protection systems. One of such factors is different air flow that could be presented as wind, draft and the like. The simulation of different air flow speeds and its influences on fire propagation in object were analyzed in this paper.

This paper proposes a new multimodal stereovision framework for wildland fires detection and analysis. The proposed system uses near infrared and visible images to robustly segment the fires and extract their three-dimensional characteristics during propagation. It uses multiple multimodal stereovision systems to capture complementary views of the fire front. A new registration approach is proposed, it uses multisensory fusion based on GNSS and IMU data to extract the projection matrix that permits the representation of the 3D reconstructed fire in a common reference frame. The fire parameters are extracted in 3D space during fire propagation using the complete reconstructed fire. The obtained results show the efficiency of the proposed system for wildland fires research and firefighting decision support in operational scenarios.

The objective of this paper is to computationally investigate the structural residual states of the peripherally supported grid structure under different fire propagation paths and reveal the path impact on the structure. The results demonstrate that the fire propagation path has a significant impact on the residual deformation of the grid structure while it has negligible impact on the distribution of residual axial member force. Hence, the structural residual states are quite different of different fire propagation paths.

With regard to fire protection for exterior walls of a building, only fire-resistive performance is considered, according to the current building standard law of Japan. In previous authors' studies, a new test method for evaluation of fire propagation along combustible cladding was proposed using primarily test specimens of facade walls with exterior thermal insulation without vent layers. In this paper, newly made results of facade fire tests also with other specimens of combustible facades, such as sandwich panels, photovoltaic sheets, combustible coating materials, and exterior insulation with vent layer, are discussed.

The subject of progressive collapse assessment in RC structures has been concerned in various studies. In contrast, most of these studies have attended to a scenario in which an instantaneous removal of a column due to unexpected impact or explosion has occurred. The present study addresses progressive collapse in RC structures resulting from both instantaneous and gradual removal of columns. The scenario for a gradual removal is the result of slow decreasing strength due to fire propagation in a specific zone of structure which is partially fire-proved. A five-story building model was selected as a case study for which the nonlinear model is later developed. Vertical displacement in the upper node of the removed column, redistribution of forces after removing the column, plastic deformations in adjoining elements, and the stress imposed on the sections of the beams adjacent to the removed column in both instantaneous and gradual cases are studied.

Fire probabilistic safety assessment (PSA) analysts have been manually determining fire-induced component failure modes and modeling them into PSA logics. These are time-consuming tasks, and may be difficult as they require a lot of information and many events should be modeled. KAERI has been developing the IPRO-ZONE (interface program for constructing zone effect table) to facilitate fire PSA works for identifying and modeling fire-induced component failure modes, and to construct a one-top fire event PSA model. A one-top fire event PSA model is automatically constructed with the output of the IPRO-ZONE, the AIMS-PSA, and internal event one-top PSA model. The output of the IPRO-ZONE includes information on fire scenarios, fire propagation areas, equipment failure modes affected by a fire, internal PSA basic events corresponding to fire-induced equipment failure modes, and the fire events to be modeled. This paper introduces the IPRO-ZONE, and its application results to fire PSAs for Ulchin Unit 3 and SMART (System-integrated Modular Advanced Reactor).

The accurate prediction of forest fire propagation is a crucial issue to minimize its effects. Several models have been developed to determine the forest fire propagation. Simulators implementing such models require diverse input parameters to deliver predictions about fire propagation. However, the data describing the actual scenario where the fire is taking place are usually subject to high levels of uncertainty. The input-data uncertainty represents a serious drawback for the correctness of the prediction. So, a two-stage methodol- ogy was developed to calibrate the input parameters in an adjustment stage so that the calibrated parameters are used in the prediction stage to improve the quality of the predictions. This way, we relieve the effects of such uncertainty. In this work, we take advantage of this two stage methodology applying Genetic Algorithms as the calibration technique. However, the use of Genetic Algorithms require the execution of many simulations. This fact, added to the eventual long executions of the underlying simulator (due to its inherent complexity), implies to deal with another serious problem: the time needed to deliver the predictions. To be useful, the prediction must be provided much faster than real time. So, it is necessary to exploit all available computing resources. In this work, we present a two-stage forest fire spread prediction hybrid MPI-OpenMP application based on the Master- Worker paradigm and the parallelization of the FARSITE simulator in order to minimize the response time. The results as regards the enhancement in the quality of the predictions are reported, as well as the results regarding the time saving obtained by this hybrid application.

In this study, combustibles investigation and fire growth rate experiment were performed for predicting initial fire behavior in buildings. Combustibles investigation was performed for residential buildings, which is most frequently affected by fire in Korea. Spatial characteristics and combustibles properties were separately investigated, and occupied area and layout characteristics of combustibles were identified to produce general layout models. Of the layout models, room was selected for fire test of a single compartment. From this test, fire propagation for each combustible was identified, which was delayed compared to the summed heat release rate of a single combustible. Also, comparison with Matsuyama model allowed improvement in the modeling of the process of fire spreading to nearby combustibles, but closer examination of ventilation factors will be required in the future.

Physical models of wildfires have been widely applied for evaluating the fire front evolution in order to obtain useful information for fire management. The main drawback in adopting such models for predicting fire propagation concerns the high computational resources that are required, especially when the analysis involves large areas or when multiple scenarios are investigated, e.g. for risk analysis purpose. This is mainly due to the complexity of phenomena involved and the necessity to use multi-dimensional approaches for the reconstruction of the fire front in the landscape. Complete two dimensional analyses can be avoided provided that possible preferential paths can be identified. Once this result is obtained, the analysis is reduced to one dimensional simulations, which can be made faster through the use of reduced models, such as POD models. In this paper, an entropy generation analysis is proposed as approach to identify preferential paths for fire propagation analysis. The analysis of the effects due to wind and slope as well as the heat transfer mechanisms, including radiation, is performed. The different contributions to the local entropy generation rate are computed in a complex scenario and the areas involving minimum and maximum total amount of entropy generation are considered for evaluating the preferential directions.

Lithium-ion cells for electronics and automotive applications have an excellent safety record. However, safety-related events can sometimes occur during routine testing of prototype designs, especially in the case of designs using new electrode materials, new separators and/or new electrolytes. High precision measurements of coulombic efficiency have recently been shown to have great value in predictions of the impact of electrolyte additives on cell lifetime. In order to apply those methods to prototype automotive cells, special compact temperature-controlled boxes were required that could maintain the temperature to ± 0.05◦C precision and ensure the safety of the laboratory. These versatile temperature-controlled boxes were designed to accommodate cells as small as coin cells and as large as 40 Ah automotive pouch cells. The ability of the design to prevent cell-to-cell fire propagation and to channel smoke and flame away from the rest of the laboratory was experimentally verified. It is hoped that the information presented

The paper presents an Unmanned Aircraft System (UAS), consisting of several aerial vehicles and a central station, for forest fire monitoring. Fire monitoring is defined as the computation in real-time of the evolution of the fire front shape and potentially other parameters related to the fire propagation, and is very important for forest fire fighting. The paper shows how an UAS can automatically obtain this information by means of on-board infrared or visual cameras. Moreover, it is shown how multiple aerial vehicles can collaborate in this application, allowing to cover bigger areas or to obtain complementary views of a fire. The paper presents results obtained in experiments considering actual controlled forest fires in quasi-operational conditions, involving a fleet of three vehicles, two autonomous helicopters and one blimp.

When performing fire PSA in a nuclear power plant, an event mapping method, using an internal event PSA model, is widely used to reduce the resources used by fire PSA model development. Feasible initiating events and component failure events due to fire are identified to transform the fault tree (FT) for an internal event PSA into one for a fire PSA using the event mapping method. A surrogate event or damage term method is used to condition the FT of the internal PSA. The surrogate event or the damage term plays the role of flagging whether the system/component in a fire compartment is damaged or not, depending on the fire being initiated from a specified compartment. These methods usually require explicit states of all compartments to be modeled in a fire area. Fire event scenarios, when using explicit identification, such as surrogate or damage terms, have two problems: (1) there is no consideration of multiple fire propagation beyond a single propagation to an adjacent compartment, and (2) there is no consideration of simultaneous fire propagations in which an initiating fire event is propagated to multiple paths simultaneously. The present paper suggests a fire propagation equation to identify all possible fire event scenarios for an explicitly treated fire event scenario in the fire PSA. Also, a method for separating fire events was developed to make all fire events a set of mutually exclusive events, which can facilitate arithmetic summation in fire risk quantification. A simple example is given to confirm the applicability of the present method for a 2x3 rectangular fire area. Also, a feasible asymptotic approach is discussed to reduce the computational burden for fire risk quantification.

Phenomena in ecosystems such as forest fires, oil spills, tornados, etc., are complex processes both in time and space. Understanding their dynamics in order to predict their future states is a challenging procedure involving the propagation of several events concerning, e.g., the transfer of energy or material. A common solution used to study such phenomena is the utilization of discrete event models and simulators. Among the phenomena studied by researchers so far, of particular interest and importance, is the forecasting of forest fire propagation since life on earth is greatly dependent on healthy forests. This paper is focused on the investigation of existing simulator models applicable in forecasting forest fire propagation. Twenty-three simulators were found in the literature and are presented here. The comparison discussion concludes with the FARSITE simulator model which is the one that stands out from the rest, and for this reason, it is investigated in depth and evaluated in a test environment.

Fire hazard studies of clean room facilities indicated that significant losses due to fire may occur in the semiconductor industry. The present study reports the results of full-scale wet bench fire tests conducted (1) to assess the fire hazards of existing wet bench materials not meeting the listing requirement of NFPA 318, (2) to assess the impact on wet bench fires of engineered materials with improved flammability characteristics, and (3) to compare the observed fire behavior with the results of simpler small- and intermediate-scale fire tests using the same materials. The full-scale wet bench fires were observed to be consistent in terms of chemical heat release rate, fire propagation, and smoke generation with the results of the small- and intermediate-scale test results. The simpler fire tests are incorporated in FM Approvals 4910 certification for materials to be used in semiconductor fabrication facilities. The small-scale test protocol is also standardized in NFPA 287. Copyright © 2008 John Wiley & Sons, Ltd.

High temporal resolution information on burnt area is needed to improve fire behaviour and emissions models.Weused the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly and active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the timing of burnt area for 16 large wildland fires. For each fire, parameters for the kriging model were defined using variogram analysis. The optimal number of observations used to estimate a pixel’s time of burning varied between four and six among the fires studied. The median standard error from kriging ranged between 0.80 and 3.56 days and the median standard error from geolocation uncertainty was between 0.34 and 2.72 days. For nine fires in the south-western US, the accuracy of the kriging model was assessed using high spatial resolution daily fire perimeter data available from the US Forest Service. For these nine fires, we also assessed the temporal reporting accuracy of the MODIS burnt area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73% of the pixels within the accuracy of a single day, compared with 33% for MCD45A1 and 53% for MCD64A1. Systematic application of this algorithm to wildland fires in the future may lead to new information about vegetation, climate and topographic controls on fire behaviour.